Implementation of Metafounders in the Genomic Prediction for the Polled Trait in Brahman Cattle Using a Multi-Breed Population.

Abstract

The absence of horns (polled trait) in cattle is associated with better animal welfare by reducing the need for dehorning. In Brahman cattle, population size and the scarcity of phenotypic records challenge the accuracy of genomic predictions for this trait. This study aimed to evaluate the genetic architecture of this trait in Brahman cattle using single-breed and multi-breed genomic prediction models, including metafounders, and to assess the influence of phenotypic classifications on heritability, prediction accuracy, bias, and dispersion. Phenotypic and genotypic data from 14 333 Nelore and Brahman animals were analyzed using threshold and linear models implemented in the BLUPF90+ software suite. Single-breed models (n = 12) were considered phenotypes (polled, scab, scur, horned), while multi-breed models (n = 10) incorporated metafounders and breed effects. Variance components were estimated via threshold models with Gibbs sampling, and predictive ability was assessed using the LR method with datasets. Single-breed models showed heritability estimates (h²) ranging from 0.56 to 0.72, but with predictive ability reflecting the Brahman population size. Multi-breed models improved predictive performance. Results were obtained with Model 20, which included alternative phenotypes, metafounders, and breed effects, yielding accuracy (0.79), reduced bias (0.36), and dispersion close to 1. These findings demonstrate that the polled trait in Brahman cattle exhibits additive genetic variability amenable to selection. The use of multi-breed analyses and metafounders enhances predictive accuracy, providing a strategy for populations and traits, and enables the inclusion of traits as genomic selection criterion to increase allele frequency in Brahman cattle and improve animal welfare.